『Researching Honesty Part 2: Can innocent mistakes explain the data?』のカバーアート

Researching Honesty Part 2: Can innocent mistakes explain the data?

Researching Honesty Part 2: Can innocent mistakes explain the data?

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概要
 Does cheating make you more creative? A provocative study from Harvard Business School suggested that it does. But data detectives uncovered suspicious patterns in the results, and a Harvard investigation found even more troubling changes in the data. In Part 2 of our investigation into the Francesca Gino research misconduct case, we dig into the now-retracted “Evil Genius” study and the suspicious changes that made its results look better, then turn to Harvard law professor Lawrence Lessig's defense of Gino: Could innocent mistakes by “an army of research assistants” explain what happened? Along the way, we explore the trap of circular reasoning in statistics, why good data management matters, and how much responsibility researchers bear for their data even when it's out of their hands.Statistical topicsStatistical sleuthingData forensicsData integrityData cleaningData managementReproducibilityStatistical significanceSpreadsheetsPredictor variablesOutcome variablesCircular reasoningResearch misconductMethodologic Morals“You cannot define your predictor variable using your outcome variable.”“If it takes an army of research assistants to clean your data, you're probably doing something wrong and maybe you need a statistician.”“Being too smart to commit stupid fraud is not a defense. Smart people do stupid things all the time.”“The more hoops your explanation has to jump through, the less convincing it becomes.”ReferencesGino F, Wiltermuth SS. Evil genius? How dishonesty can lead to greater creativity. Psychol Sci. 2014;25(4):973-981. Retracted. doi:10.1177/0956797614520714Retraction notice: Evil genius? How dishonesty can lead to greater creativity. Psychol Sci. 2023;34(8):947. doi:10.1177/09567976231187595Simonsohn U, Simmons JP, Nelson LD. Data falsificada (part 3): “The cheaters are out of order.” Data Colada. June 23, 2023. https://datacolada.org/111Simonsohn U, Simmons JP, Nelson LD. Exhibits 3, 4, and 5. Data Colada. September 16, 2023. https://datacolada.org/114Simmons JP. Harvard's Gino report reveals how a dataset was altered. Data Colada. July 9, 2024. https://datacolada.org/118Lessig L. The Gino Case. Website and podcast series presenting arguments challenging Harvard's research misconduct findings. https://theginocase.info/Simonsohn U, Simmons JP, Nelson LD. Data Falsificada. ResearchBox. Research data, analysis code, and supporting materials accompanying the Data Colada investigations. https://researchbox.org/1630.34Harvard Business School. Investigative report concerning allegations of research misconduct involving Francesca Gino. Harvard Business School Research Integrity Investigation Report. 2023. Accessed October 18, 2026. https://datacolada.org/wp-content/uploads/Harvard-Report-on-Gino.pdfKristin and Regina’s online courses: Demystifying Data: A Modern Approach to Statistical Understanding Clinical Trials: Design, Strategy, and Analysis Medical Statistics Certificate Program Writing in the Sciences Epidemiology and Clinical Research Graduate Certificate Program Program that Kristin teaches in::Epidemiology and Clinical Research Graduate Certificate Program Kristin’s manuscript writing course:https://instats.org/seminar/from-data-to-discussion-writing-a-scientFind us on:Kristin - LinkedIn & Twitter/XRegina - LinkedIn & ReginaNuzzo.com(00:00) - Intro(06:50) - The Claim: Superstars and Fraud(08:09) - Lessig’s Army of Research Assistants(22:15) - Sorted Data and 13 Suspicious Values(27:32) - Harvard’s Recovered Files from Gino’s Laptop(30:30) - Twelve People Reclassified as Cheaters(34:01) - Four RAT Totals That Don’t Add Up(45:25) - Lessig’s Research Assistant Theory(49:03) - Circular Logic and the Googling Defense(01:04:39) - Where the Evidence Leaves Us(01:07:18) - Rating the Claim(01:09:38) - Methodological Morals
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